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Trinity Large Thinking pricing and routing profile

Trinity Large Thinking from Arcee Ai lists at $0.25 per million input tokens and $0.80 per million output tokens, with a 262,144-token context window. Prices from OpenRouter's catalogue on 2026-09-28.

Input, per 1M tokens$0.25
Output, per 1M tokens$0.80
Cached input, per 1M$0.06
Context window262K
Confidence signalNot exposed

Tool callingReasoning control

Cost per 1,000 requests

Request shapeList cost
Classification or routing (600 tokens in, 10 out)$0.158
Chat reply (2,000 in, 400 out)$0.82
Retrieval-augmented answer (8,000 in, 500 out)$2.40

Before prompt caching. Try your own shape in the cost calculator.

Can Gimbix route to it first?

Not as a first-answer model through OpenRouter: no host returns token log probabilities for Trinity Large Thinking. It can still be the model Gimbix falls back to when a cheaper model is unsure.

Cheaper models that can answer first

Models priced below Trinity Large Thinking that expose a confidence signal. Whether they answer your traffic as well is what a Gimbix pilot measures.

ModelInput / output per 1MCheaper on a chat reply
Llama 4 Maverick$0.188 / $0.65222%
Qwen3 Coder Next$0.12 / $0.8032%
Qwen3 VL 30B A3B Instruct$0.15 / $0.6034%
gpt-oss-120b$0.15 / $0.6034%
GPT-4o-mini$0.15 / $0.6034%
GPT-4o-mini (2024-07-18)$0.15 / $0.6034%

Questions

How much does Trinity Large Thinking cost?

Trinity Large Thinking lists at $0.25 per million input tokens and $0.80 per million output tokens on OpenRouter as of 2026-09-28. A typical chat reply of 2,000 input and 400 output tokens costs about $0.82 per 1,000 requests.

What is the context window of Trinity Large Thinking?

262,144 tokens.

Can a cheaper model replace Trinity Large Thinking?

Sometimes. Gimbix proves it on your own traffic before routing: the cheaper model must match Trinity Large Thinking on one half of your requests and make at most three answers worse on the other.